The present invention relates to a method for analyzing diffusion-weighted magnetic resonance (MR) images recorded with a variable amount of velocity compensation to quantify the amount and velocity of blood flowing in the tissue microvasculature.
Both molecular diffusion and perfusion, i.e., blood flowing in the orientationally disordered capillary network, lead to attenuation of the signal intensity in diffusion-weighted MR imaging, an effect known as “intravoxel incoherent motion” (IVIM). Pioneered by the work of Le Bihan (1), the pseudo-diffusion coefficient D* of the flowing water, the perfusion fraction f, and the diffusion coefficient D of the non-flowing extra- and intracellular water are estimated by biexponential analysis of diffusion-weighted MR images recorded as a function of the diffusion-weighting variable b. Such an analysis has recently been applied to breast cancer (2) and liver cirrhosis (3), indicating that the perfusion parameters (D* and f) could be useful for diagnosing pathological conditions in which the blood flow in the microvasculature is altered. The values off range from 4% in brain to 25% in the pancreas (4). The analysis is hampered by the well-known problem of extracting exponential components with similar decay constants from noisy multi-exponential signal attenuation data (5). In order to obtain sufficient difference between D, which is independent of the diffusion time, and D*, which is approximately proportional to the diffusion time, diffusion-weighting is often performed at long echo times, e.g. 100 ms, thus leading to additional signal reduction and influence of noise due to nuclear spin-spin relaxation.
The signal attenuation originating from perfusion can partially be removed by employing diffusion-weighting gradient modulation schemes in which the phase shifts of spins flowing at a constant velocity are refocused (6-8). Images obtained by taking the difference of flow-compensated and non-compensated images yield information on capillary density (6, 7). Unfortunately, the image signal-to-noise ratio (SNR) is usually too low to accurately quantify pathologically induced changes of intravascular fractions using analysis methods based on difference images.
The inordinate sensitivity to noise of currently existing protocols for signal acquisition and analysis (biexponential fit to signal vs. b data or difference images of flow-compensated and non-compensated data) have so far prevented a widespread clinical use of the potentially informative perfusion parameters. Based on the considerations above, it would be desirable to have the means for obtaining these parameters with greater accuracy and less sensitivity to noise than possible with currently existing methods.
U.S. Pat. No. 7,336,072 a method for visualizing macroscopic flow in MRI is presented. The method provides analysis of data obtained by the flow compensated and non-compensated sequence. The information about macroscopic flow (velocity) is contained in the phase of the signal and it is extracted by the method disclosed in U.S. Pat. No. 7,336,072. Based on the signal phase information, the velocity filed is constructed to visualize macroscopic flow. Different visualization methods are presented in U.S. Pat. No. 7,336,072, e.g. using color coded maps or vector fields. For comprehensive flow image data reading, the velocity field is superimposed on an anatomical image. To identify regions with flow and stationary tissue, the magnitudes of the signals acquired by flow compensated and non-compensated sequences are subtracted.